Traumatic brain injury (TBI) is a significant public health concern with annual costs estimated in the billions. In the United States alone, almost 1.7 million new cases of TBI present to emergency departments or require hospitalization each year. The gross majority (˜75%) of TBI cases are classified as mild in severity with peak incidence in infants and young children and in late adolescence and early adulthood. Of the confirmed early and late adolescent TBIs, over 170,000 were due to sports and recreation. Within the range of mild TBI, it is reported that 15% will not have symptom resolution following a single mild brain injury. Thus, it is important to diagnose TBI as early as possible so that proper treatment plans can be adopted during the recovery process. Additionally, once diagnosed, it is important to track an individual's symptoms of TBI over time so that the treatment plans can be adjusted, as necessary.
Conventional systems of diagnosing TBI are directed to the quantification of symptoms of TBI. For example, these systems may determine the number and location of lesions on an individual's brain. However, there is no association between this information and the degree of severity. Accordingly, it is desired to produce a system for TBI assessment which provides for qualification of severity, along with quantification of related information.